This is an application for competitive renewal of our project entitled Contrast MRI and Chronic Myocardial Injury in Humans, which yielded many of the original papers in delayed-enhancement MRI (DE-MRI), a technique that is now considered a fundamental component of the Cardiac MRI examination and used world-wide to evaluate patients with heart disease. Despite the successes, there remain crucial limitations in the evidence base and in the technique itself. First, very few prognostic studies have been performed, and as such, there is a paucity of evidence linking DE-MRI findings with patient outcome. Yet, prognostic studies are the bedrock of evidence-based clinical medicine and these will be vital in determining the exact role of DE-MRI in assisting patient management decisions. Second, DE-MRI exhibits excellent contrast between infarcted and normal myocardium; however, the contrast between infarcted myocardium and the blood pool (both of which are bright) is frequently suboptimal. Since a large proportion of infarctions caused by coronary heart disease are subendocardial, it is often difficult to detect small infarcts or, even if detected, to assess the precise size of the infarct. Given these limitations, we have identified two important next steps that we will tackle as part of our continuing project. First, we will aim to establish the prognostic implications of the DE-MRI findings. We propose to study patients with left ventricular dysfunction due to cardiomyopathy, a group at increased risk for sudden death (Aim 1). We hypothesize that an assessment of myocardial scarring by DE-MRI will provide additional prognostic information compared with a traditional assessment, including left ventricular ejection fraction. Second, we have developed a novel dark-blood DE-MRI technique (FIDDLE), which improves the detection of subendocardial infarcts. Our goal will be to optimize this technique in an animal model of myocardial infarction (MI), and then to compare this technique with conventional DE-MRI in a study of patients with documented non-Q-wave MI, which are often small and subendocardial (Aims 2 and 3). We hypothesize that FIDDLE will improve sensitivity for detecting MI, without reducing specificity. Given the worldwide epidemic of cardiovascular disease (30% of global deaths), a noninvasive technique that could improve the detection, risk stratification, and management of patients with heart disease would represent a significant advance. Accordingly, we believe that the results of this project could have a large clinical impact.